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International Conference on Business Process Management

BPM 2016: Business Process Management Workshops pp 305–315Cite as

Social-Data Driven Sales Processes in Local Clothing Retail Stores

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 256))

Abstract

Local clothing retailers compete with online retailers but have difficulties to increase cross-selling revenues. Therefore, a data-driven sales process is conceptualized that uses data from social software in order to increase revenue. It identifies and tracks the customer using RFIDs in customer loyalty cards. By these means, social data can be used in all phases of the purchase and both for major and minor purchases. Individual product suggestions and offerings can be tailored. Local retailers are able to catch up with online retailers in their cross- and upselling revenues. In consequence, local retailers are able to stay competitive.

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Author information

Authors and Affiliations

  1. Hochschule München, Lothstr. 64, 80335, Munich, Germany

    Rainer Schmidt

  2. Hochschule Aalen, Beethovenstr. 1, 73430, Aalen, Germany

    Barbara Keller, Michael Möhring & Ralf-Christian Härting

  3. Reutlingen University, Alteburgstr. 150, 72762, Reutlingen, Germany

    Alfred Zimmermann

Authors
  1. Barbara Keller
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  2. Rainer Schmidt
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  3. Michael Möhring
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  4. Ralf-Christian Härting
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  5. Alfred Zimmermann
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Corresponding author

Correspondence to Barbara Keller .

Editor information

Editors and Affiliations

  1. Institute of Databases and Information Systems, University of Ulm, Ulm, Germany

    Manfred Reichert

  2. Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Hajo A. Reijers

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Keller, B., Schmidt, R., Möhring, M., Härting, RC., Zimmermann, A. (2016). Social-Data Driven Sales Processes in Local Clothing Retail Stores. In: Reichert, M., Reijers, H. (eds) Business Process Management Workshops. BPM 2016. Lecture Notes in Business Information Processing, vol 256. Springer, Cham. https://doi.org/10.1007/978-3-319-42887-1_25

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  • DOI: https://doi.org/10.1007/978-3-319-42887-1_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42886-4

  • Online ISBN: 978-3-319-42887-1

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